Machine Learning Engineer, Reinforcement Learning

Job summary

Responsibilities

At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within…

• Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
• Design and conduct experiments to train RL models and conduct real-world tests.
• Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training.
• Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment.
• Analyze and interpret experimental results, iterating on model design to achieve desired performance.

What they're looking for

• BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
• Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
• Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).
• Strong background in algorithms, data structures, and software engineering principles.
• Experience with physics simulation engines and tools for training RL.

Tech stack

• Python
• C++
• PyTorch
• TensorFlow
• JAX